Product Engineer (MLOps)

This position involves designing, prototyping, implementing, evaluating, and optimizing data systems to generate sports datasets and predictions with high accuracy and low latency. Responsibilities include evaluating internal modeling frameworks and tools to optimize data scientist's modeling workflow, building, testing, deploying, and maintaining production systems, and collaborating with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages. Support maintenance and optimization of cloud-native EDW and ETL solutions.